An efficient method for inverse dynamics of manipulators based on the virtual work principle

The computational efficiency of inverse dynamics of a manipulator is important to the real-time control of the system. For serial manipulators, the recursive Newton-Euler method has been proven to be the most efficient. However, for more general manipulators, such as serial manipulators with closed kinematic loops or parallel manipulators, it must be modified accordingly and the resultant computational efficiency is degraded. This article presents a computationally efficient scheme based on the virtual work principle for inverse dynamics of general manipulators. The present method uses a forward recursive scheme to compute velocities and accelerations, the Newton-Euler equation to calculate inertia forces/torque, and the virtual work principle to formulate the dynamic equations of motion. This method is equally effective for serial and parallel manipulators. For serial manipulators, its computational efficiency is comparable to the recursive Newton-Euler method. For parallel manipulators or serial manipulators with closed kinematic loops, it is more efficient than the existing methods. As an example, the computations of inverse dynamics (including inverse kinematics) of a general Stewart platform require only 842 multiplications, 511 additions, and 12 square roots.     

Two approaches for feedforward control and optimal design of underactuated multibody systems

An underactuated multibody system has less control inputs than degrees of freedom. For trajectory tracking, often a feedforward control is necessary. Two different approaches for feedforward control design are presented. The first approach is based on a coordinate transformation into the nonlinear input–output normal-form. The second approach uses servo-constraints and results in a set of differential algebraic equations. A comparison shows that both feedforward control designs have a similar structure. The analysis of the mechanical design of underactuated multibody systems might show that they are nonminimum phase, i.e., they have unstable internal dynamics. Then the feedforward control cannot be computed by time integration and output trajectory tracking becomes a very challenging task. Therefore, based on the two presented feedforward control design approaches, it is shown that through the use of an optimization procedure underactuated multibody systems can be designed in such a way that they are minimum phase. Thus, feedforward control design using the two approaches is significantly simplified.     

An algorithm for the inverse dynamics of n-axis general manipulators using Kane''s equations

Presented in this paper is an algorithm for the numerical solution of the inverse dynamics of robotic manipulators of the serial type, but otherwise arbitrary. The algorithm is applicable to manipulators containing n joints of the rotational or the prismatic type. For a given set of Hartenbeg-Denavit and inertial parameters, as well as for a given trajectory in the space of joint coordinates, the algorithm produces the time histories of the n torques or forces required to drive the manipulator through the prescribed trajectory. The algorithm is based on Kane's dynamical equations of mechanical multibody systems. Moreover, the complexity of the algorithm pressented here is lower than that of the most efficient inverse-dynamics algorithm reported in the literature. Finally, the applicability of the algorithm is illustrated with two fully solved examples.     

A Unified Formulation for Massively Parallel Rigid Multibody Dynamics of O(log2n) Computational Complexity

A novel algorithm for the solution of the inverse dynamics problem is presented and augmented to the solution of the equations of motion (EOM) for rigid multibody chains using explicit constraint components of force. The unified model corresponds to an optimal, strictly parallel, time, space, and processor lower bound solution to the dynamics of accelerated rigid multibodies, i.e., computation time of O(log₂n) using O(n) processors for an n body system. Complex topological structures are supported in the form of multiple degree-of-freedom (DOF) joints/hinges, free-floating, hyper-branched, and/or closed-chain systems, with applications ranging from multibody molecular dynamics simulations and computational molecular nanotechnology, to real-time control and simulation of spatial robotic manipulators. In addition to the theoretical significance, the algorithms presented are shown to be very efficient for practical implementation on MIMD parallel architectures for large-scale systems.     

Hybrid force and motion control of flexible joint parallel manipulators using inverse dynamics approach

An inverse dynamics control algorithm is developed for hybrid motion and contact force trajectory tracking control of flexible joint parallel manipulators. First, an open-tree structure is considered by the disconnection of adequate number of unactuated joints. The loop closure constraint equations are then included. Elimination of the joint reaction forces and the other intermediate variables yield a fourth-order relation between the actuator torques and the end-effector position and contact force variables, showing that the control torques do not have an instantaneous effect on the end-effector contact forces and accelerations because of the flexibility. The proposed control law provides simultaneous and asymptotically stable control of the end-effector contact forces and the motion along the constraint surfaces by utilizing the feedback of positions and velocities of the actuated joints and rotors. A two degree of freedom planar parallel manipulator is considered as an example to illustrate the effectiveness of the method.     

Iterative learning control with advanced output data for nonlinear non-minimum phase systems

This paper investigates iterative learning control of nonlinear discrete time non-minimum phase systems in tracking problems. The main objective of this paper is to find an input-to-output mapping in order to stabilize the non-minimum phase systems and to obtain an input update law for handling uncertain systems. In conventional approaches on the tracking of non-minimum phase systems, zero dynamics is stabilized from the system equations and the input is calculated from the state information. For the learning of uncertain systems, conventional approaches depend on the output-to-state and state-to-input mappings. In the proposed method, the inverse system is stabilized using the input-to-output mapping for nonlinear non-minimum phase systems. A new input update law is proposed based on the relative degree and the number of non-minimum phase zeros. This makes the overall proposed learning system have a simple structure as in the classical ILC.     

Inverse Dyamics of Non-Minimum Phase Systems with Non-Zero Initial Conditions

A method is presented forcomputing the inverse dynamics of a linear non-minimum phasesystem with non-zero initial conditions. The method is also usedto change or correct a trajectory after it is already in motion,and consequently, it will allow for real time control by continuallyupdating the inverse dynamics computation.Frequency domain techniques are used to compute the input functionneeded to produce a desired output trajectory at a particulardegree of freedom. An output profile based on the differencebetween the desired trajectory and either a homogeneous responseor a forced response to a previous forcing function is used tocompute the required input function. The resulting input functionactively damps out initial conditions in the system and makesit track the desired trajectory.The method is applied to a non-collocated single-link flexiblerobot arm. The finite element method using Timoshenko beam theoryis used to discretize the equations of motion. Torque profilesare computed to control the tip displacement for several problems.The first problem is to control the tip to a desired trajectorywhen starting with non-zero initial conditions. The second problemis to change the desired trajectory while the previous desiredtrajectory is already in motion. The third problem is to correctthe trajectory after a disturbance is added to the system. Thefourth problem is to analyze sensitivity to errors in the modeland initial conditions. The last problem is to compare tip responsesfor rigid and flexible link assumptions in the inverse dynamicscomputation.     

Underactuated Flexible Aerial Manipulators: a New Framework for Optimal Trajectory Planning Under Constraints Induced by Complex Dynamics

The aerial manipulators (AMs) are a new class of unmanned aerial systems (UASs) that are created in response to the ever-increasing demand for autonomous object transportation and manipulation. Because of power supply restrictions, the load carrying capacity is limited and therefore it is necessary to reduce the overall weight of these UASs. The past works in the field of AMs consider the multi-rotor unmanned aerial vehicles (UAVs) as the base and manipulators with rigid links as the interactive elements with the environment which are bulky and heavy. To overcome the issue, this paper introduces the AMs endowed with flexible manipulators, their dynamic modeling, a new method for trajectory planning and control algorithm such that the unfavorable effects of using flexible elements like vibrations are minimized. Due to lack of kinematic constraints and the presence of flexibility conditions, conventional methods of trajectory planning for ground wheeled-mobile manipulators (GWMMs) such as extended and augmented Jacobian matrix cannot be applied to AMs. The addition of flexibility to the manipulator increases underactuation degrees (UADs), the complexity of trajectory planning and control synthesis. Considering large deformation assumption for flexible links, the dynamic equations and their induced nonholonomic constraints are derived applying Lagrangian formulation. Then, these constraints with that part of equations of motion corresponding to the links flexibility are solved simultaneously in the context of an optimization algorithm resulting in optimized trajectories. Through simulation results, the proposed method of trajectory planning and vibration control of underactuated flexible AMs has been shown to be effective.     

Software for global dynamics evaluation of mechanisms

The paper deals with the multibody system software which implements the solution of the global dynamic problem for multibody systems described by redundant coordinates (DAE equations) and with a possibility of redundant number of actuators. The aim of the global dynamics evaluation is mainly the machine synthesis. The necessity of such formulation arises especially in robotics where the accessible velocities and accelerations on the given trajectory are important for the motion planning and for the design optimization of robots and manipulators. The analogical problem can be very important also for the design of any other machine type. The developed software is therefore one of the important tools for the multiobjective machine synthesis.     

Internal Preload Control of Redundantly Actuated Parallel Manipulators—Its Application to Backlash Avoiding Control

Redundant actuation of parallel manipulators can lead to internal forces without generating end-effector forces (preload). Preload can be controlled in order to prevent backlash during the manipulator motion. Such control is based on the inverse dynamics. The general solution of the inverse dynamics of redundantly actuated parallel manipulators is given. For the special case of simple overactuation an explicit solution is derived in terms of a single preload parameter. With this formulation a computational efficient open-loop preload control is developed and applied to the elimination of backlash. Its simplicity makes it applicable in real-time applications. Results are given for a planar 4RRR manipulator and a spatial heptapod.     

Extension of the divide-and-conquer algorithm for the efficient inverse dynamics analysis of multibody systems

This paper presents a new mathematical framework to extend the Generalized Divide-and-Conquer Algorithm (GDCA) for the inverse dynamics analysis of fully actuated constrained multibody systems. Inverse-GDCA (iGDCA) is a highly parallelizable method which does not create the mass and Jacobian matrices of the entire system. In this technique, generalized driving forces and constraint loads due to kinematic pairs are clearly and separately differentiated from each other in the equations of motion. As such, it can be easily used for control scheme purposes. iGDCA works based on a series of recursive assembly and disassembly passes to form and solve the equations governing the inverse dynamics of the system. Herein, the mathematical formulations to efficiently combine the dynamics of consecutive bodies in the assembly pass for the purpose of inverse dynamics analysis are presented. This is followed by generating the disassembly pass algorithm to efficiently compute generalized actuating forces. Furthermore, this paper presents necessary mathematical formulations to efficiently treat the inverse dynamics of multibody systems involving kinematic loops with various active and passive boundary conditions. This is followed by the design of a new strategy to efficiently perform the assembly–disassembly pass in these complex systems while avoiding unnecessary computations. Finally, the presented method is applied to selected open-chain and closed-chain multibody systems.     

A unified approach for inverse and direct dynamics of constrained multibody systems based on linear projection operator: applications to control and simulation

This paper presents a unified approach for inverse and direct dynamics of constrained multibody systems that can serve as a basis for analysis, simulation, and control. The main advantage of the dynamics formulation is that it does not require the constraint equations to be linearly independent. Thus, a simulation may proceed even in the presence of redundant constraints or singular configurations, and a controller does not need to change its structure whenever the mechanical system changes its topology or number of degrees of freedom. A motion-control scheme is proposed based on a projected inverse-dynamics scheme which proves to be stable and minimizes the weighted Euclidean norm of the actuation force. The projection-based control scheme is further developed for constrained systems, e.g., parallel manipulators, which have some joints with no actuators (passive joints). This is complemented by the development of constraint force control. A condition on the inertia matrix resulting in a decoupled mechanical system is analytically derived that simplifies the implementation of the force control. Finally, numerical and experimental results obtained from dynamic simulation and control of constrained mechanical systems, based on the proposed inverse and direct dynamics formulations, are documented.     

非最小相位系统的基函数型自适应迭代学习控制

针对重复运行的未知非最小相位系统的轨迹跟踪问题, 结合时域稳定逆特点, 提出了一种新的基函数型自适应迭代学习控制(Basis function based adaptive iterative learning control, BFAILC)算法. 该算法在迭代控制过程中应用自适应迭代学习辨识算法估计基函数模型, 采用伪逆型学习律逼近系统的稳定逆, 保证了迭代学习控制的收敛性和鲁棒性. 以傅里叶基函数为例, 通过在非最小相位系统上的控制仿真, 验证了算法的有效性.     

非线性非最小相位系统的控制研究综述

非线性非最小相位系统是指具有不稳定零动态或内部动态的非线性系统, 其本身固有的非最小相位特性限制了许多常规非线性控制方法(如反推控制、反馈线性化、滑模控制等)的直接应用. 因此, 非最小相位系统的控制比最小相位系统要困难得多, 是控制理论与工程应用中具有挑战性的课题之一. 本文综述了目前非线性非最小相位系统的研究成果, 着重介绍了非最小相位系统的成因、特性、 理想内模求解等问题, 并对其镇定、轨迹跟踪及路径跟踪等控制方法进行了分析比较. 最后, 讨论了非线性非最小相位系统研究领域中尚存在的问题, 并对其未来发展方向进行了展望.     

Nonlinear Trajectory Control of Multi-body Aerial Manipulators

This paper studies trajectory control of aerial vehicles equipped with robotic manipulators. The proposed approach employs free-flying multi-body dynamics modeling and backstepping control to develop stabilizing control laws for a class of underactuated aerial systems. Two control methods are developed: coordinate-based and coordinate-free which are both generally applicable to aerial manipulation tasks. A simulated hexrotor vehicle equipped with a simple manipulator is employed to demonstrate the proposed techniques.     

Flexible Links Manipulators: from Modelling to Control

This paper relates recent results obtained in the field of modelling and control of flexible link manipulators and proposes an investigation of the problem raised by this type of systems (at least in the planar case). First, adopting the modal floating frame approach and the Newton–Euler formalism, we propose an extension of the models for control to the case of fast dynamics and finite deformations. This dynamic model is based on a nonlinear generalisation of the standard Euler–Bernoulli kinematics. Then, based on the models recalled we treat the end-effector tracking problem for the one-link case as well as for the planar multi-link case. For the one-link system, we propose two methods, the first one is based on causal stable inversion of linear non-minimum phase model via output trajectory planning. The other one is an algebraic scheme, based on the parametrization of linear differential operators. For the planar multi-link case the control law proposed is based on causal stable inversion over a bounded time domain of nonlinear non-minimum phase systems. Numerical tests are presented together with experimental results, displaying the well behaved of these approaches.     

An efficient direct differentiation approach for sensitivity analysis of flexible multibody systems

This paper presents a recursive direct differentiation method for sensitivity analysis of flexible multibody systems. Large rotations and translations in the system are modeled as rigid body degrees of freedom while the deformation field within each body is approximated by superposition of modal shape functions. The equations of motion for the flexible members are differentiated at body level and the sensitivity information is generated via a recursive divide and conquer scheme. The number of differentiations required in this method is minimal. The method works concurrently with the forward dynamics simulation of the system and requires minimum data storage. The use of divide and conquer framework makes the method linear and logarithmic in complexity for serial and parallel implementation, respectively, and ideally suited for general topologies. The method is applied to a flexible two arm robotic manipulator to calculate sensitivity information and the results are compared with the finite difference approach.     

Singularities in motion and displacement functions for a 7 degree-of-freedom manipulator

The authors propose a method for the determination of singularities in motion and displacement functions for a seven degree-of-freedom manipulator. The manipulator is considered, hereby, as a set of six degree-of-freedom manipulators. It is proven that two types of singularities in motion can occur at link positions that are independent and dependent with respect to the trajectory to be executed. The relations between the structure of singularity equations and displacement equations are discussed. The derivation of displacement equations for a manipulator with singularities of the second type is based on the idea of modeling of a manipulator by two open kinematic chains and invariants that may be found for these chains. The inverse kinematic equations and the equations of singularities in motion have been derived using a symbolic computer program which can handle manipulators of general structure (with five, six, and seven degrees-of-freedom). This program is written in the Symbolic Computation Language REDUCE.     

柔性机械臂运动轨迹的鲁棒自适应控制

本文针对多连杆柔性机械臂的运动轨迹问题，讨论了动力学建模，控制系统结构设计以及鲁棒自适应控制法，运用假设模记方法得到了柔性机械臂动力学所似方程，通过对柔性机械臂动力学特性分析，建立了等价动力学模型，依此提出了一种鲁棒自适应控制算法，并给出仿真研究结果。